OpenVLA-OFT
OpenVLA collaboration
An optimized OpenVLA fine-tuning recipe with continuous action chunks, multi-image input, and faster high-frequency control.
Fine-tuning speed
Treat as an OpenVLA release/recipe in the future series schema, despite the current flat static index.
A model hub link is a declaration. Files, loadability, evaluation, and deployment are scored separately.
Model decision scorecard
Use-case scores and evidence confidence are separate; Unknown is not treated as failure.
Code, weights, and checkpoints
UsefulCode is linked; public loadable weights are not verified.
Loading and training reproducibility
UnknownNo verified loading configuration is available.
Training data requirements
UsefulRequired signal categories are declared; exact tensor and action interfaces still need verification.
Evaluation evidence
UsefulEvaluation focus is declared, but metrics are not independently verified.
Deployment readiness
UnknownHardware, latency, dependencies, and runtime loading are not yet verified.
Artifact facts and provenance
No metadata-verified artifact facts yet. Source links remain declarations only.
Loop signal demand
Signals this model family needs for training, evaluation, or failure mining.
Observation / ego video
observation · camera pose · Multiple camera views
Language intent / task phase
language intent · Task-specific robot demonstrations · Task success
Action / robot state
actions · robot state · Continuous action chunks · Bimanual high-frequency control
Future state / dynamics
VLA
Feedback / correction / failure
Task success
Sim-real / embodiment metadata
robot state · camera pose · Task-specific robot demonstrations
Evaluation focus
- Fine-tuning speed
- Inference latency
- Bimanual high-frequency control
- Task success
Missing critical loop signals
Core signal demands are represented. Check quality, alignment, and access constraints.
Related catalog datasets
BridgeData V2
Language- and goal-conditioned manipulation
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
DROID
In-the-wild real-world robot manipulation
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
Open X-Embodiment
Cross-embodiment robot learning in a unified format
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
OpenBot notes
- Treat as an OpenVLA release/recipe in the future series schema, despite the current flat static index.